Color indexing is a technique by which images in the database could be retrieved on the bases of their color content. In this paper, we propose a new set of color features for representing color images, and show how t...
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Color indexing is a technique by which images in the database could be retrieved on the bases of their color content. In this paper, we propose a new set of color features for representing color images, and show how they can be computed and used efficiently to retrieve images that possess certain similarity. these features are based on the first three moments of each color channel. Two differences distinguish this work from previous work reported in the literature. First, we compute the third moment of the color channel distribution around the second moment not around the first moment. the second moment is less sensitive to small luminance changes, than the first moment. Second we combine all three moment values in a single descriptor. this reduces the number of floating point values needed to index the image and hence speeds up the search. To give the user flexibility in terms of defining his center of attention during query time, the proposed approach divides the image into five geometrical regions and allows the user to give different weights for each region to designate its importance. the approach has been tested on databases of 205 images of airplanes and natural scenes. It proved to be insensitive to small rotations and small translations in the image and yielded a better hit rate than similar algorithms previously reported in the literature.
A highly integrated wavelet-based image management system is proposed. three solutions for key aspect of image management are derived: content-based imageretrieval (CBIR);image compression/decompression;and image tra...
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A highly integrated wavelet-based image management system is proposed. three solutions for key aspect of image management are derived: content-based imageretrieval (CBIR);image compression/decompression;and image transmission. By exploring the excellent features of wavelet, integrating key aspect of image management, the system shows a high overall performance.
A scheme that reduces the needed storage considerably without reducing the retrieval effectiveness of a content-based imageretrieval (CBIR) system such as ASSERT is introduced. this scheme enables ASSERT to retrieve ...
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A scheme that reduces the needed storage considerably without reducing the retrieval effectiveness of a content-based imageretrieval (CBIR) system such as ASSERT is introduced. this scheme enables ASSERT to retrieve the most similar physician-marked key images from the other patients, and those adjacent images that cohere withthe key images. Only the key images and the other images that cohere withthe key images are retained for archival purposes. this significantly reduces the amount of storage needed for fast retrieval.
A new system, the so-called MUVIS, is introduced for content-based indexing and retrieval for image database management systems. In addition to traditional indexing by key words, MUVIS allows indexing of objects and i...
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A new system, the so-called MUVIS, is introduced for content-based indexing and retrieval for image database management systems. In addition to traditional indexing by key words, MUVIS allows indexing of objects and images based on color, texture, shape and objects layout inside them. Due to the use of large vector features, the pyramid trees are employed to create the index structure.
Enabling the efficient storage, access and retrieval of large volumes of multi-dimensional data is one of the important emerging problems in databases. We present a framework for adaptively storing, accessing, and ret...
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Enabling the efficient storage, access and retrieval of large volumes of multi-dimensional data is one of the important emerging problems in databases. We present a framework for adaptively storing, accessing, and retrieving large images. the framework uses a space and frequency graph to generate and select image view elements for storing in the database. By adapting to user access patterns, the system selects and stores those view elements that yield the lowest average cost for accessing the multi-resolution sub-region image views. the system uses a second adaptation strategy to divide computation between server and client in progressive retrieval of image views using view elements. We show that the system speeds-up retrieval for access and retrieval modes such as drill-down browsing and remote zooming and panning and minimizes the amount of data transfer over the network.
the detection of shot boundaries in video sequences is an important task for generating indexed videodatabases. this paper provides a comprehensive quantitative comparison of the metrics that have been applied to sho...
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the detection of shot boundaries in video sequences is an important task for generating indexed videodatabases. this paper provides a comprehensive quantitative comparison of the metrics that have been applied to shot boundary detection. In addition, several standardized statistical tests that have not been applied to this problem, and three new metrics, are considered. A mathematical framework for quantitatively comparing metrics is supplied. Experimental results based on a video database containing 39,000 frames are included.
this paper is concerned with estimating a probability density function of human skin color using a finite Gaussian mixture model whose parameters are estimated through the EM algorithm. Hawkins' statistical test o...
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this paper is concerned with estimating a probability density function of human skin color using a finite Gaussian mixture model whose parameters are estimated through the EM algorithm. Hawkins' statistical test on the normality and homoscedasticity (common covariance matrix) of the estimated Gaussian mixture models is performed and McLachlan's bootstrap method is used to test the number of components in a mixture. Experimental results show that the estimated Gaussian mixture model fits skin images from a large database. Applications of the estimated density function in image and videodatabases are presented.
A prototype of the content-based imageretrieval system is implemented based on the algorithms introduced in this paper. the image contents at the high levels are extracted. the fuzzy C-means classifier is employed to...
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A prototype of the content-based imageretrieval system is implemented based on the algorithms introduced in this paper. the image contents at the high levels are extracted. the fuzzy C-means classifier is employed to compute the object clusters and provide useful information for overlapped clusters. the automatic image segmentation and categorisation is achieved. To obtain the context for imageretrieval, the subjective context and the objective context are modelled by means of the fuzzy sets theory. the system is able to trace the users' interactions during retrieval. the refinements of the retrieval results can be made while the users are submitting the queries telling the specific requirements.
In this paper, we present an approach to clustering video sequences and images for efficient retrieval using relative entropy as our cost criterion. In addition, our experiments indicate that relative entropy is a goo...
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In this paper, we present an approach to clustering video sequences and images for efficient retrieval using relative entropy as our cost criterion. In addition, our experiments indicate that relative entropy is a good similarity measure for content-based retrieval. In our clustering work, we treat images and video as probability density functions over the extracted features. this leads us to formulate a general algorithm for clustering densities. In this context, it can be seen that an euclidean distance between features and the Kullback-Liebler (KL) divergence give equivalent clustering. In addition, the asymmetry of the KL divergence leads to another clustering. Our experiments indicate that this clustering is more robust to noise and distortions compared withthe one resulting from euclidean norm.
this paper describes an API for image searching. the attempt was to isolate the functionality of the GUI from the functionality of the image search engine. the GUI would then make calls to the image search API and cou...
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this paper describes an API for image searching. the attempt was to isolate the functionality of the GUI from the functionality of the image search engine. the GUI would then make calls to the image search API and could be used with any image search engine implementing that API. Also, different methods of specifying the initial search image are discussed as well as different methods of displaying the results, including the use of 3D using VRML.
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